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R Programming

Coursera · Johns Hopkins University · 5 HN comments

HN Academy has aggregated all Hacker News stories and comments that mention Coursera's "R Programming" from Johns Hopkins University.
Course Description

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

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This course is offered by Johns Hopkins University on the Coursera platform.
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Feb 12, 2016 · alicanb on Swirl: Learn R, in R
R programming course from John Hopkins Uni. in Coursera [1] also uses swirl. [1]
I first used swirl while taking several of the R Coursera courses from Hopkins. While the courses were fantastic, swirl was how I learned the material to be able to complete the assignments and projects.

I highly recommend using swirl if you're just getting into R. - This is the best online course I've taken. Another one I am signed up for and have already done one week of lectures (preview mode) and find very applicable is
I also found the r programming class to be super useful.
I didn't think the R course was that great. I only did the first course in the speciality but I thought the assignments didn't match the lectures very well.

I don't really know R but I still got through OK (100%) but it didn't compare well with the EdX AMPLab Spark course I did around the same time.

Learning how to learn is really cool! Best time investment I have ever made.
Thanks for posting this.
Interestingly we get a lot of mixed reviews for R Prog course:

Learning how to learn is the best course online that any one can take.

I blogged my experience with learning R here -

and with the class here -

I though Jenny Bryan's R class had more modern take on R that was significantly easier to follow.

Even with some R experience I didn't feel like I got enough information from the R Prog lectures to complete the assignments.

I've been spending the past hour on "Leaning how to learn" because of the recommendations here. I was... well, the course was definitely not quite what I expected.

What I'm seeing here is a bunch of "tricks", and a lot of "brain facts" which I would usually dismiss as pseudoscience. The course almost feels like a scam. What gives?

All of the course content is based on the hard science, but is simplified so that every one can understand. You can look at the background of one of the course instructor:
I've been doing Coursera courses for the past few years in an on/off fashion. I'm pleasantly

surprised by the courses that are more popular in this list.

I think the pattern is that the foundational or introductory courses are popular as they have a

larger audience. But it doesn't comment on the quality of the course. An interesting data point

is the social media "Share" widget that appears on the right column [0].


'Newbie' covers many experience levels - from afraid to turn the computer on to moving beyond Excel pivot table macros. People need different degrees of handholding.

Not necessarily my favorite, Coursera's Programming for Everybody [1] moves forward very very slowly. Great for some people, drying paint for others. It is taught in Python.

A course I think is great is Coursera's Introduction to Systematic Program Design [2] based on Felleisen's How to Design Programs introductory text. It is possible to register for the last session, from a year ago, and complete the work on your own. It is taught in Racket.

Another course that takes a learn-by-making approach is Coursera's Creative Programming for Digital Media & Mobile Apps [3]. It is beginner friendly and really encourages "getting into it". It is taught in Processing, and in some ways I think Processing is the ideal language for an introductory course in Software Engineering - it is pared down like Racket's student languages, provides just a pinch of Java pain, facilitates the production of really interesting output, and the environment provides a fast edit-compile-run loop.

For a person who is more oriented toward scientific or mathematical problems, Coursera's R Programming [4] might by a good fit.

Among the various Python Courses, I would probably go with Udacity's Design of Computer Programs: Programming Principles [5] because it is taught by Peter Norvig.

All that said, a book may be better than an open-enrollment class for many people, and there's a lot more variation.






Thanks! Reminding myself of her feedback I think that pacing might be a significant issue which is something I hadn't considered too much (oddly).

She's someone that has lots of computer experience but the closest she's gotten to programming before is simple Excel functions (think SUM). I think she'll be much more excited by one where she's working on "real world" stuff so I'm leaving a bit towards Creative Programming for Digital Media & Mobile Apps and hope that it spurs her to learn even more.

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